nep-rmg New Economics Papers
on Risk Management
Issue of 2014‒09‒25
thirteen papers chosen by

  1. Conditional graphical models for systemic risk measurement By Paola Cerchiello; Paolo Giudici
  2. Management Forecasts, Idiosyncratic Risk, and Information Environment By Norio Kitagawa; Shin' ya Okuda
  3. Opening discussion on banking sector risk exposures and vulnerabilities from virtual currencies: An operational risk perspective By Gareth W. Peters; Ariane Chapelle; Efstathios Panayi
  4. Risk Capital Allocation: The Lorenz Set By Jens Leth Hougaard; Aleksandrs Smilgins
  5. Systemic importance of financial institutions: from a global to a local perspective? A network theory approach By Michele Bonollo; Irene Crimaldi; Andrea Flori; Fabio Pammolli; Massimo Riccaboni
  6. Banks' Stockholdings and the Correlation between Bonds and Stocks: A Portfolio Theoretic Approach By Yoshiyuki Fukuda; Kazutoshi Kan; Yoshihiko Sugihara
  7. Do LTV and DSTI caps make banks more resilient? By M. Dietsch; C. Welter-Nicol
  8. Localising Forward Intensities for Multiperiod Corporate Default By Dedy Dwi Prastyo; Wolfgang Karl Härdle; ;
  9. Similarities and Differences between U.S. and German Regulation of the Use of Derivatives and Leverage by Mutual Funds – What Can Regulators Learn from Each Other? By GaÅ‚kiewicz, Dominika
  10. The integration of credit default swap markets in the pre and post-subprime crisis in common stochastic trends By Cathy Yi-Hsuan Chen; Wolfgang Karl Härdle; Hien Pham-Thu;
  12. Forecasting Value-at-Risk Using High Frequency Information By Tae-Hwy Lee; Huiyu Huang
  13. Does Gold Act as a Hedge or a Safe Haven for Stocks? A Smooth Transition Approach By Joscha Beckmann; Theo Berger; Robert Czudaj

  1. By: Paola Cerchiello (Department of Economics and Management, University of Pavia); Paolo Giudici (Department of Economics and Management, University of Pavia)
    Abstract: Financial network models are a useful tool to model interconnectedness and systemic risks in financial systems. They are essentially descriptive, and based on highly correlated networks. In this paper we embed them in a stochastic framework, aimed at a more parsimonious and more realistic representation. First we introduce Gaussian graphical models in the field of systemic risk modelling, thus estimating the adjacency matrix of a network in a robust and coherent way. Second, we propose a conditional graphical model that can usefully decompose correlations between financial institutions into correlations between countries and correlations between institutions, within countries. While the former may be further explained by macroeconomic variables, the latter may be further explained by idiosyncratic balance sheet indicators. We have applied our proposed methods to the largest European banks, with the aim of identifying central in situations, more subject to contagion or, conversely, whose failure could result in further distress or breakdowns in the whole system. Our results show that, in the transmission of the perceived default risk, there is a strong country effect, that reflects the weakness and the strength of the underlying economies. In addition, each country reveals specific idiosyncratic factors, with communalities among similar countries
    Keywords: Conditional independence, network models, financial risk management
    Date: 2014–09
  2. By: Norio Kitagawa (Graduate School of Business Administration, Kobe University); Shin' ya Okuda (Distribution and Communication Sciences, Osaka Gakuin University)
    Abstract: Studies have identified an increase in the level of average stock return volatility. In this paper, we use the management forecast error as a proxy for disclosure quality to investigate the relationship between management forecast errors and idiosyncratic risk, as management forecasts are important information source on the Japanese stock market. We find that management forecast error is positively related to idiosyncratic risk, suggesting that high-quality public information reduces idiosyncratic risk. Furthermore, we present evidence that management forecast error is even more positively related to the idiosyncratic risks in relatively bad information environments.
    Keywords: Management forecasts, idiosyncratic risk, information environment, quality of disclosure, Japanese stock market
    JEL: M41 G12 G14
    Date: 2013–05
  3. By: Gareth W. Peters; Ariane Chapelle; Efstathios Panayi
    Abstract: We develop the first basic Operational Risk perspective on key risk management issues associated with the development of new forms of electronic currency in the real economy. In particular, we focus on understanding the development of new risks types and the evolution of current risk types as new components of financial institutions arise to cater for an increasing demand for electronic money, micro-payment systems, Virtual money and cryptographic (Crypto) currencies. In particular, this paper proposes a framework of risk identification and assessment applied to Virtual and Crypto currencies from a banking regulation perspective. In doing so, it addresses the topical issues of understanding important key Operational Risk vulnerabilities and exposure risk drivers under the framework of the Basel II/III banking regulation, specifically associated with Virtual and Crypto currencies. This is critical to consider should such alternative currencies continue to grow in utilisation to the point that they enter into the banking sector, through commercial banks and financial institutions who are beginning to contemplate their recognition in terms of deposits, transactions and exchangeability for fiat currencies. We highlight how some of the features of Virtual and Crypto currencies are important drivers of Operational Risk, posing both management and regulatory challenges that must start to be considered and addressed both by regulators, central banks and security exchanges. In this paper we focus purely on the Operational Risk perspective of banks operating in an environment where such electronic Virtual currencies are available. Some aspects of this discussion are directly relevant now, whilst others can be understood as discussions to raise awareness of issues in Operational Risk that will arise as Virtual currency start to interact more widely in the real economy.
    Date: 2014–09
  4. By: Jens Leth Hougaard (Department of Food and Resource Economics, University of Copenhagen); Aleksandrs Smilgins (Department of Food and Resource Economics, University of Copenhagen)
    Abstract: Risk capital allocation problems have been widely discussed in the academic literature. We consider a company with multiple subunits having individual portfolios. Hence, when portfolios of subunits are merged, a diversification benefit arises: the risk of the company as a whole is smaller than the sum of the risks of the individual sub-units. The question is how to allocate the risk capital of the company among the subunits in a fair way. In this paper we propose to use the Lorenz set as an allocation method. We show that the Lorenz set is operational and coherent. Moreover, we propose a set of new axioms related directly to the problem of risk capital allocation and show that the Lorenz set satisfies these new axioms in contrast to other well-known coherent methods. Finally, we discuss how to deal with non-uniqueness of the Lorenz set.
    Keywords: Risk capital, Cost allocation, Lorenz undominated elements of the core, Coherent risk allocation, Egalitarian allocation
    Date: 2014–05
  5. By: Michele Bonollo (Credito trevigiano); Irene Crimaldi (IMT Lucca Institute for Advanced Studies); Andrea Flori (IMT Lucca Institute for Advanced Studies); Fabio Pammolli (IMT Lucca Institute for Advanced Studies); Massimo Riccaboni (IMT Lucca Institute for Advanced Studies)
    Abstract: After the systemic effects of bank defaults during the recent financial crisis, and despite a huge amount of literature over the last years to detect systemic risk, no standard methodologies have been set up until now. We aim to build a concise but comprehensive picture of the state of the art, illustrating the open issues, and outlining pathways for future research. In particular, we propose the analysis of some examples of local systems that attract the attention of the financial sector. This work is directed to both academic researchers and practitioners.
    Keywords: Systemic Risk, Counterparty Risk, Financial Networks, Basel Regulations, European Market Infrastructure Regulation
    JEL: G01 G18 G21
    Date: 2014–09
  6. By: Yoshiyuki Fukuda (Bank of Japan); Kazutoshi Kan (Bank of Japan); Yoshihiko Sugihara (Bank of Japan)
    Abstract: In this paper, we analyze the optimal asset composition ratio of stocks and bonds for a bank taking into consideration the correlation between the interest rate risk and equity risk in the financial capital market using a portfolio model. The analysis reveals that in determining the asset composition ratio in Japan, the correlation coefficient between the interest rate and stock prices as well as the stock price volatility plays a more important role than the interest rate volatility. We also show that in the present circumstances, the stockholding ratios of most financial institutions in Japan are higher than the levels calculated from the model. It is suggested that when the market is exposed to severe stress such as a surge in stock price volatility or reversal of the correlation between the interest rate and stock prices, the stockholding ratios would be even more excessive than the levels obtained from the model.
    Date: 2013–03–25
  7. By: M. Dietsch; C. Welter-Nicol
    Abstract: This study provides responses to the question of the effectiveness of Loan-To-Value (LTV) and Debt Service-To-Income (DSTI) caps to contribute to financial stability. Using a lender’s risk management perspective, the paper provides a new methodology extending the standard asymptotic single risk factor to a multifactor framework, the additional factors being linked to LTV or DSTI tranches. On the basis of a unique database containing 850 896 individual housing loans, the results demonstrate the efficiency of credit standards which constrain the households’ indebtedness. On average, credit risk tends to grow in line with the increase of LTV and DSTI tranches. But our findings show also that the relationship between the risk’s growth and the ratios’ growth is not monotonic. Portfolio credit risk culminates in tranches close to the 100% LTV and the 35% DSTI thresholds. This has implications for the calibration of LTV and DSTI caps in a macroprudential perspective.
    Keywords: thousing finance, Loan-to-Value, Debt service to Income, credit risk, economic capital.
    JEL: R31 R38 G21 G32
    Date: 2014
  8. By: Dedy Dwi Prastyo; Wolfgang Karl Härdle; ;
    Abstract: Using a local adaptive Forward Intensities Approach (FIA) we investigate multiperiod corporate defaults and other delisting schemes. The proposed approach is fully datadriven and is based on local adaptive estimation and the selection of optimal estimation windows. Time-dependent model parameters are derived by a sequential testing procedure that yields adapted predictions at every time point. Applying the proposed method to monthly data on 2000 U.S. public rms over a sample period from 1991 to 2011, we estimate default probabilities over various prediction horizons. The prediction performance is evaluated against the global FIA that employs all past observations. For the six months prediction horizon, the local adaptive FIA performs with the same accuracy as the benchmark. The default prediction power is improved for the longer horizon (one to three years). Our local adaptive method can be applied to any other specications of forward intensities.
    Keywords: Accuracy ratio; Forward default intensity; Local adaptive; Mutiperiod prediction
    JEL: C41 C53 C58 G33
    Date: 2014–09
  9. By: Gałkiewicz, Dominika
    Abstract: This study analyzes current regulation with respect to the use of derivatives and leverage by mutual funds in the U.S. and Germany. After presenting a detailed overview of U.S. and German regulations, this study thoroughly compares the level of flexibility funds have in both countries. I find that funds in the U.S. and Germany face limits on direct leverage (amount of bank borrowing) of up to 33% and 10% of their net assets, respectively. Funds can extend these limits indirectly by using derivatives beyond their net assets (e.g., by selling credit default swaps protection with a notional amount equal to their net assets). Additionally, issuer-oriented rules in the U.S. and Germany account for issuer risk differently: U.S. funds have greater discretion to undervalue derivative exposure compared to German funds. All analyses of this study reveal that under existing derivative and leverage regulation, funds in both countries are able to increase risk by using derivatives up to the point at which it is possible for them to default solely due to investments in derivatives. The results of this study are highly relevant for the public and regulators.
    Keywords: Regulation; mutual funds; leverage; derivative; credit default swaps
    JEL: G15 G18
    Date: 2014
  10. By: Cathy Yi-Hsuan Chen; Wolfgang Karl Härdle; Hien Pham-Thu;
    Abstract: It was evident that credit default swap (CDS) spreads have been highly correlated during the recent financial crisis. Motivated by this evidence, this study attempts to investigate the extent to which CDS markets across regions, maturities and credit ratings have integrated more in crisis. By applying the Panel Analysis of Non-stationarity in Idiosyncratic and Common components method (PANIC) developed by Bai and Ng (2004), we observe a potential shift in CDS integration between the pre- and post-Lehman collapse period, indicating that the system of CDS spreads is tied to a long-run equilibrium path. This finding contributes to a credit risk management task and also coincides with the missions of Basel III since the more integrated CDS markets could result in correlated default, credit contagion and simultaneous downgrading in the future.
    Keywords: Credit default swaps; cointegration; common stochastic trend; correlated default
    JEL: C38 G32 E43
    Date: 2014–08
  11. By: Joan Nix and Bruce McNevin (Department of Economics and BBA, Queens College of the City University of New York)
    Abstract: The application of the CAPM to ten S&P sectors is investigated using wavelet analysis. Wavelet methods provide a unified framework for investigating the relationship among variables at different frequencies and the evolution of these relationships over time. Betas at different time and frequency scales using wavelet analysis are estimated for ten sectors and compared to the betas estimated from a simple regression of the market model. We find coherence and frequency differences across sectors that are not reflected in the estimation of standard beta. Given that there is no a priori reason to assume that the synchronization of sector returns with market returns has only a time varying dimension, wavelet analysis by allowing for multiple time-varying frequencies offers estimates of sector level betas that capture features of the underlying risk dynamics that would be missed using the standard estimate of beta.
    Keywords: Wavelet Analysis, CAPM, Equity Betas, Standard & Poor Sectors
    Date: 2014–09
  12. By: Tae-Hwy Lee (Department of Economics, University of California Riverside); Huiyu Huang (GMO Emerging Markets)
    Abstract: In prediction of quantiles of daily S&P 500 returns we consider how we use high-frequency 5-minute data. We examine methods that incorporate the high frequency information either indirectly through combining forecasts (using forecasts generated from returns sampled at different intra-day interval) or directly through combining high frequency information into one model. We consider subsample averaging, bootstrap averaging, forecast averaging methods for the indirect case, and factor models with principal component approach for both cases. We show, in forecasting daily S&P 500 index return quantile (VaR is simply the negative of it), using high-frequency information is beneficial, often substantially and particularly so in forecasting downside risk. Our empirical results show that the averaging methods (subsample averaging, bootstrap averaging, forecast averaging), which serve as different ways of forming the ensemble average from using high frequency intraday information, provide excellent forecasting performance compared to using just low frequency daily information.
    Keywords: VaR, Quantiles, Subsample averaging, Bootstrap averaging, Forecast combination, High-frequency data.
    JEL: C53 G32 C22
    Date: 2014–09
  13. By: Joscha Beckmann; Theo Berger; Robert Czudaj
    Abstract: This study deals with the issue whether gold actually exhibits the function of a hedge or a safe haven as often referred to in the media and academia. In order to test the Baur and Lucey (2010) hypotheses, we contribute to the existing literature by the augmentation of their model to a smooth transition regression (STR) using an exponential transition function which splits the regression model into two extreme regimes. One accounts for periods in which stock returns are on average and therefore allows to test whether gold acts as a hedge for stocks, the other one accounts for periods characterized by extreme market conditions where the volatility of the stock returns is high. The latter state enables us to test whether gold can be regarded as a safe haven for stocks. The study includes a broad set of 18 individual markets as well as five regional indices and covers a sample period running from January 1970 to March 2012 on a monthly frequency. Overall, our findings show that gold serves as a hedge and a safe haven. However, this ability seems to be market-specific. In addition, by applying a portfolio analysis we also show that our findings are useful for investors.
    Keywords: Gold; hedge; safe haven; smooth transition; stock prices
    JEL: G11 G14 G15
    Date: 2014–08

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